Abstract
Pre-empting evolutionary changes in river morphology is essential for resource managers involved in strategic decision making in riverine environments, whether related to land use, flood risk alleviation, channel stability, or river restoration. Being able to better forecast and communicate expected channel morphological evolution over management timeframes is part of developing foresight competency in river management, allowing resource managers to envisage several plausible futures in channel evolution and to plan towards the most preferred. Foresight competency consists of six stages (framing-scanning-forecasting-visioning-planning-acting) of which the forecasting and visioning components are the least well developed. Development of an intermediate complexity forecasting tool, FRAME, simulating likely modes of channel morphological evolution over decadal to centennial timeframes over long distances, is the subject of a companion paper (Soar, et al. this volume). Here we focus on the weakest link in providing channel evolutionary foresight, visioning. Visioning involves translating scientific forecasts into an interactive decision support tool that supports transparent decision making. Critically, model outputs need conversion into metrics that alert managers to the likelihood of progressive or threshold-based transitions within or between channel morphology states. Bound by two constraints, namely, the ‘dimensions’ of channel morphology change supported by the numerical forecast model (here, FRAME) and the management requirements related to land-use planning, hazard diminution/asset maximization, and river conservation, seven process-based state-transition metrics are proposed. The metrics are subsequently converted into graphical indicators designed for management application and assembled into several prototype dashboard-style displays intended to facilitate interactive decision support.
A proof-of-concept application of this prototype visioning system (provisionally, RUBRIC, ‘RUles-Based morphological Response in River Channels’) is illustrated for the lower Mississippi River, simulating morphological changes under hypothetical conditions of climate stationarity, a wetter climate and flow diversion for the period 2020-2080. Dashboard displays are developed semi-automatically from the metrics calculated from the numerical model outputs and consist of multiple graphical indicators derived using Excel’s in-built graphing functions. This example illustrates a relative consistency of conditions in this heavily engineered lowland sand-bed river that will likely not be replicated in other riverine settings. Near-term priorities in developing RUBRIC towards a fully-operational decision support tool will include incorporating new forecast outputs from FRAME, improvements in dashboard design and functionality, and modifications to facilitate user interactively. Developing foresight competency for channel evolution has the potential to greatly improve strategic decision-making in river management, but it is highly demanding of the underlying database of empirical and theoretical knowledge in fluvial geomorphology.
A proof-of-concept application of this prototype visioning system (provisionally, RUBRIC, ‘RUles-Based morphological Response in River Channels’) is illustrated for the lower Mississippi River, simulating morphological changes under hypothetical conditions of climate stationarity, a wetter climate and flow diversion for the period 2020-2080. Dashboard displays are developed semi-automatically from the metrics calculated from the numerical model outputs and consist of multiple graphical indicators derived using Excel’s in-built graphing functions. This example illustrates a relative consistency of conditions in this heavily engineered lowland sand-bed river that will likely not be replicated in other riverine settings. Near-term priorities in developing RUBRIC towards a fully-operational decision support tool will include incorporating new forecast outputs from FRAME, improvements in dashboard design and functionality, and modifications to facilitate user interactively. Developing foresight competency for channel evolution has the potential to greatly improve strategic decision-making in river management, but it is highly demanding of the underlying database of empirical and theoretical knowledge in fluvial geomorphology.
Original language | English |
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Title of host publication | Proceedings of the Sedimentation and Hydrologic Modeling (SEDHYD) 2023 Conference |
Number of pages | 13 |
Publication status | Published - 12 May 2023 |
Event | Sedimentation and Hydrologic Modeling (SEDHYD) 2023 Conference - St Louis, United States Duration: 8 May 2023 → 12 May 2023 |
Conference
Conference | Sedimentation and Hydrologic Modeling (SEDHYD) 2023 Conference |
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Country/Territory | United States |
City | St Louis |
Period | 8/05/23 → 12/05/23 |